Paid Search: 5 ad groups, 10 ads, negative keywords, budget allocation Social: 5 Twitter threads, Reddit/HN posts for 5 subreddits + Show HN Display: 5 banner sets × 4 formats (leaderboard, rectangle, skyscraper, mobile) Video: 60s 'Own Your Stack' script + 30s 'The Math' script Email: 5-email nurture sequence with segmentation rules All backed by verified stats and named psych principles RoadChain-SHA2048: 3d877b6d5e4827c0 RoadChain-Identity: alexa@sovereign RoadChain-Full: 3d877b6d5e4827c0bb309d360e8632b675ea561b7af44fb5671f649dce88197b5f435f485de674ef1dd68ff273639d46c11fd6c966054ca43a3a28a64211ccab064271fb6cfde2bd2000032e5f94c01cc38717091db36c163cf268e477e6376926a9da420c622bdb1d7b44674dde3d646944f22ce86717d2d3131e4ebf8fe65263e6cbf3fad5d758f950d71f9d6eeea98fa005463907064ac161058d57e05b078b4983241f929afaf1ad5e9234f8292ecb394d5222a118b39fee751f18600308d3548b468314aac374ac2eee30890c48008a109fbb2d732f59cd03fd0b8a6439e5aa5a152540167ac8e376a043c9d5500c6f5fdd7343c7e6103f2b826ffd7565
194 lines
6.7 KiB
Markdown
194 lines
6.7 KiB
Markdown
# BlackRoad Reddit & Hacker News Posts
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**Principle:** Authority + Social Validation + Central Route (these audiences think deeply and counterargue)
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**Critical rule:** These audiences HATE marketing. Lead with technical substance. Never sound like an ad.
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---
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## Hacker News: Show HN Post
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**Title:** Show HN: I run 16 AI models on 5 Raspberry Pis — 52 TOPS, $0/month cloud bill
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**Body:**
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```
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I've been building self-hosted AI infrastructure on Raspberry Pis for the past year. Wanted to share what a production setup actually looks like.
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The stack:
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- 5x Raspberry Pi (4x Pi 5, 1x Pi 4)
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- 2x Hailo-8 M.2 AI accelerators (26 TOPS each = 52 TOPS total)
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- Ollama serving 16 models (Llama 3, Mistral, CodeLlama, Phi, Gemma, etc.)
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- Qdrant for vector search / RAG
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- NATS v2.12.3 for agent-to-agent pub/sub messaging
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- Gitea hosting 207 repos (primary git — GitHub is a mirror)
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- Docker Swarm for orchestration
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- WireGuard mesh for encryption
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- Cloudflare Tunnels for ingress (no open ports)
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- Pi-hole for DNS filtering (120+ blocked domains)
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- PostgreSQL for primary database
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This serves 30 websites across 20 domains, runs a billing system (RoadPay), processes 50 AI skills, and hosts all our code.
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Total hardware cost: ~$400
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Monthly cloud bill: $0
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Power consumption: ~46 watts
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For context: one H100 on AWS is $3.90/hr = $33,696/year. Two Hailo-8s cost $198 total and run forever.
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The project is called BlackRoad OS. Everything is at blackroad.io. Happy to answer questions about the architecture, the Hailo-8 performance, Ollama on Pi, or anything else.
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```
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---
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## Hacker News: Blog Post Submission
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**Title:** 94% of IT leaders fear vendor lock-in — the self-hosted market just hit $18.48B
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**URL:** `https://blackroad.io/blog/vendor-lock-in`
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*(No body text for URL submissions on HN)*
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---
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## Reddit: r/selfhosted
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**Title:** I replaced my entire cloud infrastructure with 5 Raspberry Pis — here's the full architecture
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**Body:**
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```
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Been running this setup for a year now. Figured I'd share since I see a lot of "is self-hosting AI actually viable?" questions here.
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**Hardware:**
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- Alice (Pi 5) — gateway, Pi-hole, PostgreSQL, Qdrant
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- Cecilia (Pi 5 + Hailo-8) — 16 Ollama models, embedding engine
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- Octavia (Pi 5 + Hailo-8) — Gitea (207 repos), Docker Swarm
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- Aria (Pi 5) — agent runtime, NATS messaging
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- Lucidia (Pi 4) — 334 web apps, CI/CD
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**Networking:**
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- WireGuard mesh between all nodes
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- Cloudflare Tunnels for external access (zero open ports)
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- Pi-hole DNS filtering fleet-wide
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**AI Stack:**
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- Ollama serves Llama 3, Mistral, CodeLlama, Phi-3, Gemma, and more
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- 2x Hailo-8 = 52 TOPS of neural inference
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- Qdrant + nomic-embed-text for RAG/semantic search
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- NATS pub/sub for agent-to-agent communication
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**What it runs:**
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- 30 websites (20 domains)
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- 50 AI skills across 6 modules
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- Billing system (Stripe for cards, D1 for everything else)
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- Auth system (JWT, 42 users)
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- Full CI/CD pipeline
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- 207 git repositories on Gitea
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**Cost:**
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- Hardware: ~$400 one-time
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- Monthly: electricity only (~$5-8)
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- Cloud bill: $0
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Happy to answer questions. The project is BlackRoad OS — blackroad.io
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```
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---
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## Reddit: r/homelab
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**Title:** My homelab runs a company — 5 Pis, 52 TOPS AI, 30 websites, $0/month
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**Body:**
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```
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I know "homelab to production" posts get mixed reactions, but this one's been running stable for a year so I figured I'd share.
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[PHOTO OF PI CLUSTER]
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**The nodes:**
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| Node | Hardware | Role |
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|------|----------|------|
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| Alice | Pi 5 8GB | Gateway, Pi-hole, PostgreSQL, Qdrant |
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| Cecilia | Pi 5 + Hailo-8 | 16 AI models (Ollama), embeddings |
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| Octavia | Pi 5 + Hailo-8 | Gitea (207 repos), Docker Swarm |
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| Aria | Pi 5 | Agent runtime, NATS pub/sub |
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| Lucidia | Pi 4 | 334 web apps, GitHub Actions |
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**Total power:** ~46W
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**Total compute:** 52 TOPS neural inference
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This serves real production traffic — 30 websites, a billing system, auth, AI inference, CI/CD, the works.
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The Hailo-8 has been the game changer. $99 for 26 TOPS of inference, plugs into the Pi 5 via M.2. Two of them outperform the economics of any cloud GPU for inference workloads.
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AMA about the setup, Hailo-8 performance, Ollama on Pi, or the network architecture.
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```
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---
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## Reddit: r/LocalLLaMA
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**Title:** Running 16 Ollama models on Raspberry Pi 5 + Hailo-8 — benchmarks and setup guide
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**Body:**
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```
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Setup: Pi 5 (8GB) + Hailo-8 M.2 (26 TOPS), running Ollama.
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**Models currently loaded:**
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- Llama 3 8B
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- Mistral 7B
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- CodeLlama 7B
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- Phi-3 Mini
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- Gemma 2B
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- Plus 11 more specialized models
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**What works well:**
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- Inference speed is surprisingly usable for 7-8B models
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- Hailo-8 handles classification/detection tasks natively at full 26 TOPS
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- Multiple models can be loaded (Ollama swaps efficiently)
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- Embedding (nomic-embed-text) runs smoothly for RAG
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**The real value:**
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Running two of these nodes (52 TOPS combined) with NATS pub/sub means agents on different Pis can communicate and delegate tasks. One node runs the LLM, another handles embeddings, a third does classification.
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It's not replacing an A100 for training. But for inference, RAG, and agent orchestration? It's production-viable and costs $200 in hardware total.
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Full architecture at blackroad.io if you want the deep dive. Happy to share configs.
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```
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---
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## Reddit: r/raspberry_pi
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**Title:** 68 million Pis sold worldwide. Here's what 5 of them do when you treat them like a data center.
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**Body:**
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```
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I've been running my entire company infrastructure on Raspberry Pis for a year. Not as a project. As production.
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- 30 websites across 20 domains
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- 207 git repositories on Gitea
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- 16 AI models via Ollama
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- 52 TOPS of neural inference (2x Hailo-8)
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- Full billing system
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- Vector database for semantic search
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- Agent mesh network (NATS pub/sub)
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- Automated CI/CD pipeline
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- Pi-hole DNS filtering
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All on 5 Pis drawing ~46 watts total.
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The gap between "hobby project" and "production infrastructure" isn't hardware. It's architecture. Docker Swarm, WireGuard mesh, Cloudflare Tunnels, proper monitoring — and suddenly a $55 SBC is a datacenter node.
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Happy to share the full setup. The project is called BlackRoad OS.
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```
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---
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## Posting Rules
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1. **Never sound like an ad.** These communities will downvote anything that smells like marketing. Lead with technical substance.
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2. **Answer every comment.** Engagement in comments drives visibility on both HN and Reddit.
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3. **Be honest about limitations.** "This isn't replacing an A100 for training" builds more credibility than overclaiming.
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4. **Include the photo.** r/homelab and r/raspberry_pi are visual. Show the actual hardware.
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5. **Time the posts.** HN: Tuesday-Thursday, 9-11am ET. Reddit: varies by sub, but weekday mornings.
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6. **Don't cross-post simultaneously.** Stagger by 2-3 days so you can customize based on what resonated.
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